nlp-projrct (2) (2).ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "3684f160",
   "metadata": {},
   "source": [
    "Import Libraries "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "e981ef4e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-10T21:53:06.579868Z",
     "iopub.status.busy": "2022-11-10T21:53:06.579046Z",
     "iopub.status.idle": "2022-11-10T21:53:08.047513Z",
     "shell.execute_reply": "2022-11-10T21:53:08.045573Z"
    },
    "id": "gOc5dvpynkF7",
    "outputId": "e803deaf-5fb6-4db5-9564-e5b2fe4b2cda",
    "papermill": {
     "duration": 1.486,
     "end_time": "2022-11-10T21:53:08.051741",
     "exception": false,
     "start_time": "2022-11-10T21:53:06.565741",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# #clean \n",
    "# import numpy as np\n",
    "# import nltk \n",
    "# import re \n",
    "# from nltk.corpus import stopwords\n",
    "# from collections import Counter\n",
    "\n",
    "# nltk.download(\"popular\")\n",
    "\n",
    "\n",
    "# #A regular expression (or RE) specifies a set of strings that matches it; the functions in this module let you check\n",
    "# #if a particular string matches a given regular expression\n",
    "# #(or if a given regular expression matches a particular string, which comes down to the same thing).\n",
    "\n",
    "\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns \n",
    "import matplotlib.pyplot as plt\n",
    "from tqdm import tqdm\n",
    "%matplotlib inline\n",
    "\n",
    "import warnings\n",
    "\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "sns.set_style('darkgrid')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "24af7543",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-10T21:53:08.072384Z",
     "iopub.status.busy": "2022-11-10T21:53:08.071893Z",
     "iopub.status.idle": "2022-11-10T21:53:08.077988Z",
     "shell.execute_reply": "2022-11-10T21:53:08.076253Z"
    },
    "id": "i8bSQeFUpsIu",
    "outputId": "bae2f80e-f171-4d34-fcf5-0ba8ed925059",
    "papermill": {
     "duration": 0.019313,
     "end_time": "2022-11-10T21:53:08.080698",
     "exception": false,
     "start_time": "2022-11-10T21:53:08.061385",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# !unzip '/content/shai-training-2022-a-level-2.zip'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8b887f19",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-10T21:53:08.101353Z",
     "iopub.status.busy": "2022-11-10T21:53:08.100829Z",
     "iopub.status.idle": "2022-11-10T21:53:09.862828Z",
     "shell.execute_reply": "2022-11-10T21:53:09.861535Z"
    },
    "papermill": {
     "duration": 1.777217,
     "end_time": "2022-11-10T21:53:09.866879",
     "exception": false,
     "start_time": "2022-11-10T21:53:08.089662",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>text</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>I enjoy watching Robert Forster. That was the ...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>You better see this episode from the beginning...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>As far as cinematography goes, this film was p...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>The opening sequence alone is worth the cost o...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Return to Cabin by the Lake is Perhaps one of ...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44995</th>\n",
       "      <td>As an avid Gone With the Wind fan, I was disap...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44996</th>\n",
       "      <td>Where this movie is faithful to Burroughs' vis...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44997</th>\n",
       "      <td>At one time `Buddy Cop' movies ruled the box o...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44998</th>\n",
       "      <td>Critics love this movie. I personally found it...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44999</th>\n",
       "      <td>The scientist Charles and his wife (or assista...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>45000 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    text  label\n",
       "0      I enjoy watching Robert Forster. That was the ...      0\n",
       "1      You better see this episode from the beginning...      1\n",
       "2      As far as cinematography goes, this film was p...      0\n",
       "3      The opening sequence alone is worth the cost o...      1\n",
       "4      Return to Cabin by the Lake is Perhaps one of ...      1\n",
       "...                                                  ...    ...\n",
       "44995  As an avid Gone With the Wind fan, I was disap...      0\n",
       "44996  Where this movie is faithful to Burroughs' vis...      1\n",
       "44997  At one time `Buddy Cop' movies ruled the box o...      1\n",
       "44998  Critics love this movie. I personally found it...      0\n",
       "44999  The scientist Charles and his wife (or assista...      0\n",
       "\n",
       "[45000 rows x 2 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train = pd.read_csv('../input/shai-training-2022-a-level-2/Train.csv')\n",
    "df_test = pd.read_csv('../input/shai-training-2022-a-level-2/Test.csv')\n",
    "df_valid = pd.read_csv('../input/shai-training-2022-a-level-2/Valid.csv')\n",
    "df = pd.concat([df_train, df_valid]).sample(frac = 1).reset_index(drop=True)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "698d4334",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-10T21:53:09.886780Z",
     "iopub.status.busy": "2022-11-10T21:53:09.886272Z",
     "iopub.status.idle": "2022-11-10T21:53:09.924650Z",
     "shell.execute_reply": "2022-11-10T21:53:09.923284Z"
    },
    "papermill": {
     "duration": 0.053232,
     "end_time": "2022-11-10T21:53:09.928936",
     "exception": false,
     "start_time": "2022-11-10T21:53:09.875704",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 45000 entries, 0 to 44999\n",
      "Data columns (total 2 columns):\n",
      " #   Column  Non-Null Count  Dtype \n",
      "---  ------  --------------  ----- \n",
      " 0   text    45000 non-null  object\n",
      " 1   label   45000 non-null  int64 \n",
      "dtypes: int64(1), object(1)\n",
      "memory usage: 703.2+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "19daeb67",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-10T21:53:09.953660Z",
     "iopub.status.busy": "2022-11-10T21:53:09.953061Z",
     "iopub.status.idle": "2022-11-10T21:53:09.979429Z",
     "shell.execute_reply": "2022-11-10T21:53:09.977436Z"
    },
    "papermill": {
     "duration": 0.041748,
     "end_time": "2022-11-10T21:53:09.983805",
     "exception": false,
     "start_time": "2022-11-10T21:53:09.942057",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "text     0\n",
       "label    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "4650005a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-10T21:53:10.009841Z",
     "iopub.status.busy": "2022-11-10T21:53:10.009152Z",
     "iopub.status.idle": "2022-11-10T21:53:10.019437Z",
     "shell.execute_reply": "2022-11-10T21:53:10.018394Z"
    },
    "papermill": {
     "duration": 0.02782,
     "end_time": "2022-11-10T21:53:10.024059",
     "exception": false,
     "start_time": "2022-11-10T21:53:09.996239",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Label 0: 0.5001% \n",
      "LABEL 1: 0.4999%\n"
     ]
    }
   ],
   "source": [
    "label_0, label_1 = df['label'].value_counts()\n",
    "\n",
    "print(f'Label 0: {(label_0/df.shape[0]):.4f}% \\nLABEL 1: {(label_1/df.shape[0]):.4f}%')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "7aed659b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-10T21:53:10.051152Z",
     "iopub.status.busy": "2022-11-10T21:53:10.049616Z",
     "iopub.status.idle": "2022-11-10T21:53:10.258243Z",
     "shell.execute_reply": "2022-11-10T21:53:10.256606Z"
    },
    "papermill": {
     "duration": 0.225123,
     "end_time": "2022-11-10T21:53:10.261775",
     "exception": false,
     "start_time": "2022-11-10T21:53:10.036652",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='label', ylabel='count'>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x=df['label'], palette = [\"c\" , \"Salmon\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "32f6dfd4",
   "metadata": {
    "papermill": {
     "duration": 0.0102,
     "end_time": "2022-11-10T21:53:10.281798",
     "exception": false,
     "start_time": "2022-11-10T21:53:10.271598",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Insights\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5da0311e",
   "metadata": {
    "papermill": {
     "duration": 0.009032,
     "end_time": "2022-11-10T21:53:10.300352",
     "exception": false,
     "start_time": "2022-11-10T21:53:10.291320",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "No need to perform any data imputation or any balancing techniques"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "26148de4",
   "metadata": {
    "papermill": {
     "duration": 0.00864,
     "end_time": "2022-11-10T21:53:10.317949",
     "exception": false,
     "start_time": "2022-11-10T21:53:10.309309",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Data Transformation\n",
    "\n",
    "Using the package nltk (natural language tool kit), I utilize different methods to transform my text data into a cleaned one which can significantly help for my model creation.\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "80d94d09",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-10T21:53:10.338442Z",
     "iopub.status.busy": "2022-11-10T21:53:10.337791Z",
     "iopub.status.idle": "2022-11-10T21:53:11.400022Z",
     "shell.execute_reply": "2022-11-10T21:53:11.398389Z"
    },
    "papermill": {
     "duration": 1.076348,
     "end_time": "2022-11-10T21:53:11.403311",
     "exception": false,
     "start_time": "2022-11-10T21:53:10.326963",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "import nltk\n",
    "from nltk.corpus import stopwords\n",
    "from nltk.stem import WordNetLemmatizer\n",
    "from nltk.tokenize import RegexpTokenizer\n",
    "from nltk.tokenize import word_tokenize\n",
    "from nltk.probability import FreqDist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "6b9af1ce",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-10T21:53:11.426202Z",
     "iopub.status.busy": "2022-11-10T21:53:11.425575Z",
     "iopub.status.idle": "2022-11-10T21:53:36.689744Z",
     "shell.execute_reply": "2022-11-10T21:53:36.687343Z"
    },
    "papermill": {
     "duration": 25.278924,
     "end_time": "2022-11-10T21:53:36.692366",
     "exception": false,
     "start_time": "2022-11-10T21:53:11.413442",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading collection 'all'\n",
      "[nltk_data]    | \n",
      "[nltk_data]    | Downloading package abc to /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package abc is already up-to-date!\n",
      "[nltk_data]    | Downloading package alpino to /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package alpino is already up-to-date!\n",
      "[nltk_data]    | Downloading package averaged_perceptron_tagger to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package averaged_perceptron_tagger is already up-\n",
      "[nltk_data]    |       to-date!\n",
      "[nltk_data]    | Downloading package averaged_perceptron_tagger_ru to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Unzipping\n",
      "[nltk_data]    |       taggers/averaged_perceptron_tagger_ru.zip.\n",
      "[nltk_data]    | Downloading package basque_grammars to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package basque_grammars is already up-to-date!\n",
      "[nltk_data]    | Downloading package biocreative_ppi to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package biocreative_ppi is already up-to-date!\n",
      "[nltk_data]    | Downloading package bllip_wsj_no_aux to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package bllip_wsj_no_aux is already up-to-date!\n",
      "[nltk_data]    | Downloading package book_grammars to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package book_grammars is already up-to-date!\n",
      "[nltk_data]    | Downloading package brown to /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package brown is already up-to-date!\n",
      "[nltk_data]    | Downloading package brown_tei to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package brown_tei is already up-to-date!\n",
      "[nltk_data]    | Downloading package cess_cat to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package cess_cat is already up-to-date!\n",
      "[nltk_data]    | Downloading package cess_esp to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package cess_esp is already up-to-date!\n",
      "[nltk_data]    | Downloading package chat80 to /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package chat80 is already up-to-date!\n",
      "[nltk_data]    | Downloading package city_database to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package city_database is already up-to-date!\n",
      "[nltk_data]    | Downloading package cmudict to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package cmudict is already up-to-date!\n",
      "[nltk_data]    | Downloading package comparative_sentences to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Unzipping corpora/comparative_sentences.zip.\n",
      "[nltk_data]    | Downloading package comtrans to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package comtrans is already up-to-date!\n",
      "[nltk_data]    | Downloading package conll2000 to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package conll2000 is already up-to-date!\n",
      "[nltk_data]    | Downloading package conll2002 to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package conll2002 is already up-to-date!\n",
      "[nltk_data]    | Downloading package conll2007 to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package conll2007 is already up-to-date!\n",
      "[nltk_data]    | Downloading package crubadan to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package crubadan is already up-to-date!\n",
      "[nltk_data]    | Downloading package dependency_treebank to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package dependency_treebank is already up-to-date!\n",
      "[nltk_data]    | Downloading package dolch to /usr/share/nltk_data...\n",
      "[nltk_data]    |   Unzipping corpora/dolch.zip.\n",
      "[nltk_data]    | Downloading package europarl_raw to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package europarl_raw is already up-to-date!\n",
      "[nltk_data]    | Downloading package extended_omw to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    | Downloading package floresta to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package floresta is already up-to-date!\n",
      "[nltk_data]    | Downloading package framenet_v15 to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Unzipping corpora/framenet_v15.zip.\n",
      "[nltk_data]    | Downloading package framenet_v17 to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Unzipping corpora/framenet_v17.zip.\n",
      "[nltk_data]    | Downloading package gazetteers to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package gazetteers is already up-to-date!\n",
      "[nltk_data]    | Downloading package genesis to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package genesis is already up-to-date!\n",
      "[nltk_data]    | Downloading package gutenberg to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package gutenberg is already up-to-date!\n",
      "[nltk_data]    | Downloading package ieer to /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package ieer is already up-to-date!\n",
      "[nltk_data]    | Downloading package inaugural to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package inaugural is already up-to-date!\n",
      "[nltk_data]    | Downloading package indian to /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package indian is already up-to-date!\n",
      "[nltk_data]    | Downloading package jeita to /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package jeita is already up-to-date!\n",
      "[nltk_data]    | Downloading package kimmo to /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package kimmo is already up-to-date!\n",
      "[nltk_data]    | Downloading package knbc to /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package knbc is already up-to-date!\n",
      "[nltk_data]    | Downloading package large_grammars to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package large_grammars is already up-to-date!\n",
      "[nltk_data]    | Downloading package lin_thesaurus to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package lin_thesaurus is already up-to-date!\n",
      "[nltk_data]    | Downloading package mac_morpho to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package mac_morpho is already up-to-date!\n",
      "[nltk_data]    | Downloading package machado to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package machado is already up-to-date!\n",
      "[nltk_data]    | Downloading package masc_tagged to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package masc_tagged is already up-to-date!\n",
      "[nltk_data]    | Downloading package maxent_ne_chunker to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package maxent_ne_chunker is already up-to-date!\n",
      "[nltk_data]    | Downloading package maxent_treebank_pos_tagger to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package maxent_treebank_pos_tagger is already up-\n",
      "[nltk_data]    |       to-date!\n",
      "[nltk_data]    | Downloading package moses_sample to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package moses_sample is already up-to-date!\n",
      "[nltk_data]    | Downloading package movie_reviews to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package movie_reviews is already up-to-date!\n",
      "[nltk_data]    | Downloading package mte_teip5 to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package mte_teip5 is already up-to-date!\n",
      "[nltk_data]    | Downloading package mwa_ppdb to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Unzipping misc/mwa_ppdb.zip.\n",
      "[nltk_data]    | Downloading package names to /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package names is already up-to-date!\n",
      "[nltk_data]    | Downloading package nombank.1.0 to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    | Downloading package nonbreaking_prefixes to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Unzipping corpora/nonbreaking_prefixes.zip.\n",
      "[nltk_data]    | Downloading package nps_chat to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package nps_chat is already up-to-date!\n",
      "[nltk_data]    | Downloading package omw to /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package omw is already up-to-date!\n",
      "[nltk_data]    | Downloading package omw-1.4 to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    | Downloading package opinion_lexicon to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package opinion_lexicon is already up-to-date!\n",
      "[nltk_data]    | Downloading package panlex_swadesh to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    | Downloading package paradigms to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package paradigms is already up-to-date!\n",
      "[nltk_data]    | Downloading package pe08 to /usr/share/nltk_data...\n",
      "[nltk_data]    |   Unzipping corpora/pe08.zip.\n",
      "[nltk_data]    | Downloading package perluniprops to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Unzipping misc/perluniprops.zip.\n",
      "[nltk_data]    | Downloading package pil to /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package pil is already up-to-date!\n",
      "[nltk_data]    | Downloading package pl196x to /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package pl196x is already up-to-date!\n",
      "[nltk_data]    | Downloading package porter_test to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package porter_test is already up-to-date!\n",
      "[nltk_data]    | Downloading package ppattach to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package ppattach is already up-to-date!\n",
      "[nltk_data]    | Downloading package problem_reports to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package problem_reports is already up-to-date!\n",
      "[nltk_data]    | Downloading package product_reviews_1 to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package product_reviews_1 is already up-to-date!\n",
      "[nltk_data]    | Downloading package product_reviews_2 to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package product_reviews_2 is already up-to-date!\n",
      "[nltk_data]    | Downloading package propbank to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package propbank is already up-to-date!\n",
      "[nltk_data]    | Downloading package pros_cons to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package pros_cons is already up-to-date!\n",
      "[nltk_data]    | Downloading package ptb to /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package ptb is already up-to-date!\n",
      "[nltk_data]    | Downloading package punkt to /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package punkt is already up-to-date!\n",
      "[nltk_data]    | Downloading package qc to /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package qc is already up-to-date!\n",
      "[nltk_data]    | Downloading package reuters to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package reuters is already up-to-date!\n",
      "[nltk_data]    | Downloading package rslp to /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package rslp is already up-to-date!\n",
      "[nltk_data]    | Downloading package rte to /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package rte is already up-to-date!\n",
      "[nltk_data]    | Downloading package sample_grammars to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package sample_grammars is already up-to-date!\n",
      "[nltk_data]    | Downloading package semcor to /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package semcor is already up-to-date!\n",
      "[nltk_data]    | Downloading package senseval to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package senseval is already up-to-date!\n",
      "[nltk_data]    | Downloading package sentence_polarity to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package sentence_polarity is already up-to-date!\n",
      "[nltk_data]    | Downloading package sentiwordnet to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package sentiwordnet is already up-to-date!\n",
      "[nltk_data]    | Downloading package shakespeare to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package shakespeare is already up-to-date!\n",
      "[nltk_data]    | Downloading package sinica_treebank to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package sinica_treebank is already up-to-date!\n",
      "[nltk_data]    | Downloading package smultron to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package smultron is already up-to-date!\n",
      "[nltk_data]    | Downloading package snowball_data to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package snowball_data is already up-to-date!\n",
      "[nltk_data]    | Downloading package spanish_grammars to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package spanish_grammars is already up-to-date!\n",
      "[nltk_data]    | Downloading package state_union to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package state_union is already up-to-date!\n",
      "[nltk_data]    | Downloading package stopwords to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package stopwords is already up-to-date!\n",
      "[nltk_data]    | Downloading package subjectivity to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package subjectivity is already up-to-date!\n",
      "[nltk_data]    | Downloading package swadesh to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package swadesh is already up-to-date!\n",
      "[nltk_data]    | Downloading package switchboard to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package switchboard is already up-to-date!\n",
      "[nltk_data]    | Downloading package tagsets to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package tagsets is already up-to-date!\n",
      "[nltk_data]    | Downloading package timit to /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package timit is already up-to-date!\n",
      "[nltk_data]    | Downloading package toolbox to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package toolbox is already up-to-date!\n",
      "[nltk_data]    | Downloading package treebank to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package treebank is already up-to-date!\n",
      "[nltk_data]    | Downloading package twitter_samples to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package twitter_samples is already up-to-date!\n",
      "[nltk_data]    | Downloading package udhr to /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package udhr is already up-to-date!\n",
      "[nltk_data]    | Downloading package udhr2 to /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package udhr2 is already up-to-date!\n",
      "[nltk_data]    | Downloading package unicode_samples to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package unicode_samples is already up-to-date!\n",
      "[nltk_data]    | Downloading package universal_tagset to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package universal_tagset is already up-to-date!\n",
      "[nltk_data]    | Downloading package universal_treebanks_v20 to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package universal_treebanks_v20 is already up-to-\n",
      "[nltk_data]    |       date!\n",
      "[nltk_data]    | Downloading package vader_lexicon to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package vader_lexicon is already up-to-date!\n",
      "[nltk_data]    | Downloading package verbnet to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package verbnet is already up-to-date!\n",
      "[nltk_data]    | Downloading package verbnet3 to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Unzipping corpora/verbnet3.zip.\n",
      "[nltk_data]    | Downloading package webtext to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package webtext is already up-to-date!\n",
      "[nltk_data]    | Downloading package wmt15_eval to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Unzipping models/wmt15_eval.zip.\n",
      "[nltk_data]    | Downloading package word2vec_sample to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package word2vec_sample is already up-to-date!\n",
      "[nltk_data]    | Downloading package wordnet to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package wordnet is already up-to-date!\n",
      "[nltk_data]    | Downloading package wordnet2021 to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    | Downloading package wordnet31 to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    | Downloading package wordnet_ic to\n",
      "[nltk_data]    |     /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package wordnet_ic is already up-to-date!\n",
      "[nltk_data]    | Downloading package words to /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package words is already up-to-date!\n",
      "[nltk_data]    | Downloading package ycoe to /usr/share/nltk_data...\n",
      "[nltk_data]    |   Package ycoe is already up-to-date!\n",
      "[nltk_data]    | \n",
      "[nltk_data]  Done downloading collection all\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import nltk\n",
    "nltk.download('all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "1b7e9343",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-10T21:53:36.719627Z",
     "iopub.status.busy": "2022-11-10T21:53:36.718851Z",
     "iopub.status.idle": "2022-11-10T21:53:36.726666Z",
     "shell.execute_reply": "2022-11-10T21:53:36.725423Z"
    },
    "papermill": {
     "duration": 0.025129,
     "end_time": "2022-11-10T21:53:36.729719",
     "exception": false,
     "start_time": "2022-11-10T21:53:36.704590",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def clean_tokenize_stop(text):\n",
    "    \n",
    "    #Removes Unnecessary characters and only collects alphabets or numbers\n",
    "    regexp = RegexpTokenizer('\\w+')\n",
    "    cleaned = regexp.tokenize(text.lower()) #transform text into lower cases\n",
    "        \n",
    "    #Removing stopwords or common words which dont add any meaning\n",
    "    stopwords = nltk.corpus.stopwords.words(\"english\")\n",
    "    stopwords.extend(['movies', 'movie', 'im', 'film', 'br']) #extending my stopwords\n",
    "    cleaned2 = [item for item in cleaned if item not in stopwords]\n",
    "    \n",
    "    #Performing lemmatization(reverting a word to its base form) which is better than stemming \n",
    "    wordnet_lem = WordNetLemmatizer()\n",
    "    cleaned3 = [wordnet_lem.lemmatize(item) for item in cleaned2] # running runs\n",
    "    \n",
    "    cleaned4 = ' '.join([word for word in cleaned3]) \n",
    "                \n",
    "    return cleaned4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "5c98e152",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-10T21:53:36.757763Z",
     "iopub.status.busy": "2022-11-10T21:53:36.757273Z",
     "iopub.status.idle": "2022-11-10T21:54:45.110247Z",
     "shell.execute_reply": "2022-11-10T21:54:45.108880Z"
    },
    "papermill": {
     "duration": 68.370171,
     "end_time": "2022-11-10T21:54:45.113317",
     "exception": false,
     "start_time": "2022-11-10T21:53:36.743146",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "df['text'] = df['text'].apply(clean_tokenize_stop)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "b7d36dd1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-10T21:54:45.138424Z",
     "iopub.status.busy": "2022-11-10T21:54:45.138028Z",
     "iopub.status.idle": "2022-11-10T21:54:45.154708Z",
     "shell.execute_reply": "2022-11-10T21:54:45.151883Z"
    },
    "papermill": {
     "duration": 0.032194,
     "end_time": "2022-11-10T21:54:45.157540",
     "exception": false,
     "start_time": "2022-11-10T21:54:45.125346",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>text</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>enjoy watching robert forster main reason rent...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>better see episode beginning start watch later...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>far cinematography go pretty good mid 50 time ...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>opening sequence alone worth cost admission ch...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>return cabin lake perhaps one sequel live orig...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44995</th>\n",
       "      <td>avid gone wind fan disappointed watch original...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44996</th>\n",
       "      <td>faithful burroughs vision excellent departs bu...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44997</th>\n",
       "      <td>one time buddy cop ruled box office seemed eve...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44998</th>\n",
       "      <td>critic love personally found senseless tastele...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44999</th>\n",
       "      <td>scientist charles wife assistant marissa recei...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>45000 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    text  label\n",
       "0      enjoy watching robert forster main reason rent...      0\n",
       "1      better see episode beginning start watch later...      1\n",
       "2      far cinematography go pretty good mid 50 time ...      0\n",
       "3      opening sequence alone worth cost admission ch...      1\n",
       "4      return cabin lake perhaps one sequel live orig...      1\n",
       "...                                                  ...    ...\n",
       "44995  avid gone wind fan disappointed watch original...      0\n",
       "44996  faithful burroughs vision excellent departs bu...      1\n",
       "44997  one time buddy cop ruled box office seemed eve...      1\n",
       "44998  critic love personally found senseless tastele...      0\n",
       "44999  scientist charles wife assistant marissa recei...      0\n",
       "\n",
       "[45000 rows x 2 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6bc53bcc",
   "metadata": {
    "papermill": {
     "duration": 0.011161,
     "end_time": "2022-11-10T21:54:45.180938",
     "exception": false,
     "start_time": "2022-11-10T21:54:45.169777",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Words Frequency Distribution\n",
    "\n",
    "Im going to plot the frequency or the number of times the word appeared in the corpus.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "cfe4b3f8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-10T21:54:45.205944Z",
     "iopub.status.busy": "2022-11-10T21:54:45.205496Z",
     "iopub.status.idle": "2022-11-10T21:55:10.837826Z",
     "shell.execute_reply": "2022-11-10T21:55:10.836043Z"
    },
    "papermill": {
     "duration": 25.649494,
     "end_time": "2022-11-10T21:55:10.841928",
     "exception": false,
     "start_time": "2022-11-10T21:54:45.192434",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "from nltk.tokenize import word_tokenize\n",
    "from nltk.probability import FreqDist\n",
    "\n",
    "allwords = ' '.join([word for word in df['text']]) # ['feel', 'family']\n",
    "words = word_tokenize(allwords)\n",
    "fd = FreqDist(words)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c6f3933d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-10T21:55:10.870798Z",
     "iopub.status.busy": "2022-11-10T21:55:10.869286Z",
     "iopub.status.idle": "2022-11-10T21:55:12.295298Z",
     "shell.execute_reply": "2022-11-10T21:55:12.294061Z"
    },
    "papermill": {
     "duration": 1.442672,
     "end_time": "2022-11-10T21:55:12.298179",
     "exception": false,
     "start_time": "2022-11-10T21:55:10.855507",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Frequency Distribution Counts'}, xlabel='Samples', ylabel='Counts'>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Plotting the frequency counts\n",
    "plt.figure(figsize=(12,8))\n",
    "plt.title('Frequency Distribution Counts', fontdict={'size': 20})\n",
    "plt.xlabel('Words', fontdict={'size': 18})\n",
    "plt.ylabel('Counts', fontdict={'size': 18})\n",
    "fd.plot(50, cumulative =False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "7ed0acb8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-10T21:55:12.325611Z",
     "iopub.status.busy": "2022-11-10T21:55:12.325138Z",
     "iopub.status.idle": "2022-11-10T21:56:00.993883Z",
     "shell.execute_reply": "2022-11-10T21:56:00.992786Z"
    },
    "papermill": {
     "duration": 48.689501,
     "end_time": "2022-11-10T21:56:01.000564",
     "exception": false,
     "start_time": "2022-11-10T21:55:12.311063",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-0.5, 799.5, 499.5, -0.5)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plotting some word Cloud\n",
    "from wordcloud import WordCloud\n",
    "\n",
    "wordcloud = WordCloud(width=800, \n",
    "                     height=500, \n",
    "                     random_state=2, \n",
    "                     max_font_size=100).generate(allwords)\n",
    "\n",
    "plt.figure(figsize=(10, 7))\n",
    "plt.imshow(wordcloud, interpolation='bilinear')\n",
    "plt.axis('off')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71f3c9ea",
   "metadata": {
    "papermill": {
     "duration": 0.017456,
     "end_time": "2022-11-10T21:56:01.036748",
     "exception": false,
     "start_time": "2022-11-10T21:56:01.019292",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Model Creation\n",
    "\n",
    "Splitting of data part where i will train my Sentiment Analysis model predictor using Tf-idf Vectorizer and utilizing 5 machine learning techniques with the use of pipeline to make my code clean.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "d0afdecf",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-10T21:56:01.075952Z",
     "iopub.status.busy": "2022-11-10T21:56:01.075231Z",
     "iopub.status.idle": "2022-11-10T21:56:01.260486Z",
     "shell.execute_reply": "2022-11-10T21:56:01.258902Z"
    },
    "papermill": {
     "duration": 0.207955,
     "end_time": "2022-11-10T21:56:01.263531",
     "exception": false,
     "start_time": "2022-11-10T21:56:01.055576",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.feature_extraction.text import TfidfVectorizer\n",
    "\n",
    "from sklearn.naive_bayes import MultinomialNB\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.ensemble import GradientBoostingClassifier\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n",
    "from sklearn.svm import LinearSVC\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "43596989",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-10T21:56:01.299603Z",
     "iopub.status.busy": "2022-11-10T21:56:01.299161Z",
     "iopub.status.idle": "2022-11-10T21:56:01.316198Z",
     "shell.execute_reply": "2022-11-10T21:56:01.314885Z"
    },
    "papermill": {
     "duration": 0.038227,
     "end_time": "2022-11-10T21:56:01.318954",
     "exception": false,
     "start_time": "2022-11-10T21:56:01.280727",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "x = df['text']\n",
    "y = df['label']\n",
    "x_train, x_test, y_train, y_test = train_test_split(x,y, test_size=0.3) #test size is 30%"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "869f6ca0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-10T21:56:01.355226Z",
     "iopub.status.busy": "2022-11-10T21:56:01.354822Z",
     "iopub.status.idle": "2022-11-10T21:56:01.377973Z",
     "shell.execute_reply": "2022-11-10T21:56:01.376337Z"
    },
    "papermill": {
     "duration": 0.044974,
     "end_time": "2022-11-10T21:56:01.380825",
     "exception": false,
     "start_time": "2022-11-10T21:56:01.335851",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Pipeline(steps=[('cv1', TfidfVectorizer()), ('NB', MultinomialNB())]),\n",
       " Pipeline(steps=[('cv2', TfidfVectorizer()), ('LR', LogisticRegression())]),\n",
       " Pipeline(steps=[('cv3', TfidfVectorizer()),\n",
       "                 ('GB', GradientBoostingClassifier())]),\n",
       " Pipeline(steps=[('cv4', TfidfVectorizer()), ('RF', RandomForestClassifier())]),\n",
       " Pipeline(steps=[('cv5', TfidfVectorizer()), ('DT', KNeighborsClassifier())]),\n",
       " Pipeline(steps=[('cv6', TfidfVectorizer()), ('LS', LinearSVC())])]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Pipeline creation \n",
    "\n",
    "pipe_NB = Pipeline([\n",
    "    ('cv1', TfidfVectorizer()),\n",
    "    ('NB', MultinomialNB())\n",
    "])\n",
    "\n",
    "pipe_LR = Pipeline([\n",
    "    ('cv2', TfidfVectorizer()),\n",
    "    ('LR', LogisticRegression())\n",
    "])\n",
    "\n",
    "pipe_GB = Pipeline([\n",
    "    ('cv3', TfidfVectorizer()),\n",
    "    ('GB', GradientBoostingClassifier())\n",
    "])\n",
    "\n",
    "pipe_RF = Pipeline([\n",
    "    ('cv4', TfidfVectorizer()),\n",
    "    ('RF', RandomForestClassifier())\n",
    "])\n",
    "\n",
    "pipe_KNN = Pipeline([\n",
    "    ('cv5', TfidfVectorizer()),\n",
    "    ('DT', KNeighborsClassifier())\n",
    "])\n",
    "\n",
    "# pipe_LA = Pipeline([\n",
    "#     ('cv6', TfidfVectorizer()),\n",
    "#     ('LA', LinearDiscriminantAnalysis())\n",
    "# ])\n",
    "\n",
    "pipe_LS = Pipeline([\n",
    "    ('cv6', TfidfVectorizer()),\n",
    "    ('LS', LinearSVC())\n",
    "])\n",
    "\n",
    "# pipe_HC = Pipeline([\n",
    "#     ('cv7', TfidfVectorizer()),\n",
    "#     ('HC', HistGradientBoostingClassifier())\n",
    "# ])\n",
    "\n",
    "pipelines = [pipe_NB, pipe_LR, pipe_GB, pipe_RF, pipe_KNN ,pipe_LS ]\n",
    "pipelines"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d3e834c8",
   "metadata": {
    "papermill": {
     "duration": 0.016659,
     "end_time": "2022-11-10T21:56:01.414281",
     "exception": false,
     "start_time": "2022-11-10T21:56:01.397622",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Model Evaluation Part\n",
    "\n",
    "I used accuracy as a metric because the dataset is balance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "769ae6c9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-10T21:56:01.451157Z",
     "iopub.status.busy": "2022-11-10T21:56:01.450624Z",
     "iopub.status.idle": "2022-11-10T22:03:12.368999Z",
     "shell.execute_reply": "2022-11-10T22:03:12.367529Z"
    },
    "papermill": {
     "duration": 430.940614,
     "end_time": "2022-11-10T22:03:12.372494",
     "exception": false,
     "start_time": "2022-11-10T21:56:01.431880",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 6/6 [07:10<00:00, 71.75s/it]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Accuracy (percentage)')"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Data Fitting and Testing\n",
    "pipe_names = ['Multinomial Naive Bayes', 'Logistic Regression', 'Gradient Boosting', 'Random Forest', 'KNN',\n",
    "'Linear SVC']\n",
    "train_acc = []\n",
    "val_acc = []\n",
    "\n",
    "for pipe in tqdm(pipelines):\n",
    "    pipe.fit(x_train, y_train)\n",
    "    train_acc.append(pipe.score(x_train, y_train)*100)\n",
    "    val_acc.append(pipe.score(x_test, y_test)*100)\n",
    "    \n",
    "data_acc = pd.DataFrame({\n",
    "    'names': pipe_names + pipe_names, # [naive,logistic, ...., navive]\n",
    "    'score': train_acc + val_acc, # [98,97,...,87,88]\n",
    "    'label' : (['train']*6) + (['test']*6) # [train, train, train, ..., test,test] \n",
    "})\n",
    "\n",
    "plt.figure(figsize=(15,8))\n",
    "plt.title('Accuracy scores between each Algorithms', fontdict={'fontsize':25})\n",
    "sns.barplot(data= data_acc, x='names', y='score', hue='label')\n",
    "plt.xlabel('Model Names', fontdict={'fontsize':20})\n",
    "plt.yticks(range(0,105,6))\n",
    "plt.ylabel('Accuracy (percentage)', fontdict={'fontsize':20})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e5db1d3",
   "metadata": {
    "papermill": {
     "duration": 0.021015,
     "end_time": "2022-11-10T22:03:12.414456",
     "exception": false,
     "start_time": "2022-11-10T22:03:12.393441",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Optimization\n",
    "\n",
    "### Based from the accuracy above, The top 3 models are Naive Bayes, Logistic Regression and Random Forest\n",
    "\n",
    "These three models will undergo hyper parameter tuning to see which is the best model out of all three.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "ea2caf85",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-10T22:03:12.460572Z",
     "iopub.status.busy": "2022-11-10T22:03:12.458511Z",
     "iopub.status.idle": "2022-11-11T00:43:32.513041Z",
     "shell.execute_reply": "2022-11-11T00:43:32.509309Z"
    },
    "papermill": {
     "duration": 9620.083241,
     "end_time": "2022-11-11T00:43:32.518494",
     "exception": false,
     "start_time": "2022-11-10T22:03:12.435253",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "from sklearn.model_selection import GridSearchCV, cross_val_score\n",
    "\n",
    "\n",
    "# Create a pipeline\n",
    "param_range = [5, 10, 15]\n",
    "param_range_fl = [0.1, 1, 3]\n",
    "ngram_range = [(1,3), (2,2)]\n",
    "\n",
    "pipe = Pipeline([('Vectorizer', TfidfVectorizer())\n",
    "                ,(\"classifier\", RandomForestClassifier())])\n",
    "\n",
    "grid_param = [\n",
    "                {\"Vectorizer\": [TfidfVectorizer()],\n",
    "                 \"Vectorizer__ngram_range\": ngram_range,\n",
    "                \"classifier\": [LinearSVC()]\n",
    "                 },\n",
    "                {\n",
    "                \"Vectorizer\": [TfidfVectorizer()],\n",
    "                 \"Vectorizer__ngram_range\": ngram_range,\n",
    "                \"classifier\": [LogisticRegression()],\n",
    "                 \"classifier__penalty\": ['l1', 'l2'],\n",
    "                 \"classifier__C\": param_range_fl\n",
    "                 },\n",
    "                {\n",
    "                 \"Vectorizer\": [TfidfVectorizer()],\n",
    "                 \"Vectorizer__ngram_range\": ngram_range,\n",
    "                \"classifier\": [RandomForestClassifier()],\n",
    "                 \"classifier__max_depth\": param_range,\n",
    "                 \"classifier__min_samples_split\": param_range\n",
    "                }]\n",
    "\n",
    "gridsearch = GridSearchCV(pipe, grid_param, cv=15, n_jobs=-1, scoring='accuracy') \n",
    "best_model = gridsearch.fit(x_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "06982167",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-11T00:43:32.569828Z",
     "iopub.status.busy": "2022-11-11T00:43:32.569302Z",
     "iopub.status.idle": "2022-11-11T00:43:32.615757Z",
     "shell.execute_reply": "2022-11-11T00:43:32.614150Z"
    },
    "papermill": {
     "duration": 0.074852,
     "end_time": "2022-11-11T00:43:32.618910",
     "exception": false,
     "start_time": "2022-11-11T00:43:32.544058",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean_fit_time</th>\n",
       "      <th>param_classifier</th>\n",
       "      <th>mean_test_score</th>\n",
       "      <th>rank_test_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>83.373055</td>\n",
       "      <td>LinearSVC()</td>\n",
       "      <td>0.896794</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>166.225850</td>\n",
       "      <td>LogisticRegression()</td>\n",
       "      <td>0.888159</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>187.251264</td>\n",
       "      <td>LogisticRegression()</td>\n",
       "      <td>0.879048</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>31.768384</td>\n",
       "      <td>LinearSVC()</td>\n",
       "      <td>0.866540</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>77.680459</td>\n",
       "      <td>LogisticRegression()</td>\n",
       "      <td>0.859651</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    mean_fit_time      param_classifier  mean_test_score  rank_test_score\n",
       "0       83.373055           LinearSVC()         0.896794                1\n",
       "7      166.225850  LogisticRegression()         0.888159                2\n",
       "5      187.251264  LogisticRegression()         0.879048                3\n",
       "1       31.768384           LinearSVC()         0.866540                4\n",
       "13      77.680459  LogisticRegression()         0.859651                5"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cols = ['mean_fit_time', 'param_classifier', 'mean_test_score', 'rank_test_score']\n",
    "pd.DataFrame(best_model.cv_results_)[cols].sort_values(by='rank_test_score').head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "15a8e3a8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-11T00:43:32.662945Z",
     "iopub.status.busy": "2022-11-11T00:43:32.662398Z",
     "iopub.status.idle": "2022-11-11T00:43:32.674263Z",
     "shell.execute_reply": "2022-11-11T00:43:32.672900Z"
    },
    "papermill": {
     "duration": 0.037293,
     "end_time": "2022-11-11T00:43:32.677050",
     "exception": false,
     "start_time": "2022-11-11T00:43:32.639757",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Vectorizer': TfidfVectorizer(ngram_range=(1, 3)),\n",
       " 'Vectorizer__ngram_range': (1, 3),\n",
       " 'classifier': LinearSVC()}"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "best_model.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "97885d09",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-11T00:43:32.720119Z",
     "iopub.status.busy": "2022-11-11T00:43:32.719618Z",
     "iopub.status.idle": "2022-11-11T00:44:41.545049Z",
     "shell.execute_reply": "2022-11-11T00:44:41.543693Z"
    },
    "papermill": {
     "duration": 68.868719,
     "end_time": "2022-11-11T00:44:41.565993",
     "exception": false,
     "start_time": "2022-11-11T00:43:32.697274",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Pipeline(steps=[('cv1', TfidfVectorizer(ngram_range=(1, 3))),\n",
       "                ('LS', LinearSVC())])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "best_model = Pipeline([\n",
    "    ('cv1', TfidfVectorizer(ngram_range=(1,3))),\n",
    "    ('LS', LinearSVC())\n",
    "])\n",
    "best_model.fit(x_train, y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d8888f36",
   "metadata": {
    "papermill": {
     "duration": 0.019495,
     "end_time": "2022-11-11T00:44:41.605478",
     "exception": false,
     "start_time": "2022-11-11T00:44:41.585983",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "f2d79ca8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-11T00:44:41.650526Z",
     "iopub.status.busy": "2022-11-11T00:44:41.649384Z",
     "iopub.status.idle": "2022-11-11T00:44:41.754038Z",
     "shell.execute_reply": "2022-11-11T00:44:41.752679Z"
    },
    "papermill": {
     "duration": 0.130309,
     "end_time": "2022-11-11T00:44:41.757116",
     "exception": false,
     "start_time": "2022-11-11T00:44:41.626807",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "df_check = pd.read_csv('../input/shai-training-2022-a-level-2/Test.csv')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "02472679",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-11T00:44:41.799562Z",
     "iopub.status.busy": "2022-11-11T00:44:41.799087Z",
     "iopub.status.idle": "2022-11-11T00:44:41.824632Z",
     "shell.execute_reply": "2022-11-11T00:44:41.821591Z"
    },
    "papermill": {
     "duration": 0.052263,
     "end_time": "2022-11-11T00:44:41.829490",
     "exception": false,
     "start_time": "2022-11-11T00:44:41.777227",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 5000 entries, 0 to 4999\n",
      "Data columns (total 3 columns):\n",
      " #   Column  Non-Null Count  Dtype  \n",
      "---  ------  --------------  -----  \n",
      " 0   id      5000 non-null   int64  \n",
      " 1   text    5000 non-null   object \n",
      " 2   label   0 non-null      float64\n",
      "dtypes: float64(1), int64(1), object(1)\n",
      "memory usage: 117.3+ KB\n"
     ]
    }
   ],
   "source": [
    "df_check.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "cd42c9d6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-11T00:44:41.878078Z",
     "iopub.status.busy": "2022-11-11T00:44:41.876916Z",
     "iopub.status.idle": "2022-11-11T00:44:49.171317Z",
     "shell.execute_reply": "2022-11-11T00:44:49.170102Z"
    },
    "papermill": {
     "duration": 7.322442,
     "end_time": "2022-11-11T00:44:49.174716",
     "exception": false,
     "start_time": "2022-11-11T00:44:41.852274",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "x_test_t = df_check['text'].apply(clean_tokenize_stop)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "af8b8c13",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-11T00:44:49.219062Z",
     "iopub.status.busy": "2022-11-11T00:44:49.218627Z",
     "iopub.status.idle": "2022-11-11T00:44:49.224285Z",
     "shell.execute_reply": "2022-11-11T00:44:49.223090Z"
    },
    "papermill": {
     "duration": 0.031092,
     "end_time": "2022-11-11T00:44:49.226806",
     "exception": false,
     "start_time": "2022-11-11T00:44:49.195714",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# df_check = pd.read_csv('../input/shai-training-2022-a-level-2/Test.csv')\n",
    "# x_test_t = df_check['text'].apply(clean_tokenize_stop)\n",
    "y_test_t = df_check['label']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "bab429ca",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-11T00:44:49.271326Z",
     "iopub.status.busy": "2022-11-11T00:44:49.270875Z",
     "iopub.status.idle": "2022-11-11T00:44:52.080098Z",
     "shell.execute_reply": "2022-11-11T00:44:52.078548Z"
    },
    "papermill": {
     "duration": 2.83563,
     "end_time": "2022-11-11T00:44:52.083406",
     "exception": false,
     "start_time": "2022-11-11T00:44:49.247776",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "y_pred =best_model.predict(x_test_t)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "7b459494",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-11T00:44:52.131592Z",
     "iopub.status.busy": "2022-11-11T00:44:52.130052Z",
     "iopub.status.idle": "2022-11-11T00:44:52.170007Z",
     "shell.execute_reply": "2022-11-11T00:44:52.169088Z"
    },
    "papermill": {
     "duration": 0.06639,
     "end_time": "2022-11-11T00:44:52.172385",
     "exception": false,
     "start_time": "2022-11-11T00:44:52.105995",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id  label\n",
       "0   0      0\n",
       "1   1      0\n",
       "2   2      0\n",
       "3   3      1\n",
       "4   4      0"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "submission_file = pd.read_csv(\"../input/shai-training-2022-a-level-2/sample_submission.csv\")\n",
    "submission_file['label'] = y_pred.round().astype(int)\n",
    "submission_file.to_csv('submission.csv', index=False)\n",
    "submission_file.head()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.12"
  },
  "papermill": {
   "default_parameters": {},
   "duration": 10321.875732,
   "end_time": "2022-11-11T00:44:55.145927",
   "environment_variables": {},
   "exception": null,
   "input_path": "__notebook__.ipynb",
   "output_path": "__notebook__.ipynb",
   "parameters": {},
   "start_time": "2022-11-10T21:52:53.270195",
   "version": "2.3.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}